Daily skin-to-skin contact in full-term infants and breastfeeding: Secondary outcomes from a randomized controlled trial

This randomized controlled trial evaluated the effect of a 5-week daily skin-to-skin contact (SSC) intervention between mothers and their full-term infants, compared with care-as-usual, on exclusive and continued breastfeeding duration during the first post-natal year. Healthy pregnant women (n = 116) from a community sample were enrolled and randomly allocated to the SSC or care-as-usual condition. SSC mothers were requested to provide one daily hour of SSC for the first five post-natal weeks. Twelve months post-partum, mothers indicated the number of exclusive and continued breastfeeding months. Multiple regression analyses were conducted using intention-to-treat, per-protocol and exploratory dose–response frameworks. In intention-to-treat analyses, exclusive and continued breastfeeding duration was not different between groups (exclusive: 3.61 ± 1.99 vs. 3.16 ± 1.77 months; adjusted mean difference 0.28, 95% confidence interval [CI] ?0.33 to 0.89; p = 0.36; continued: 7.98 ± 4.20 vs. 6.75 ± 4.06 months; adjusted mean difference 0.81, 95% CI ?0.46 to 2.08; p = 0.21). In per-protocol analyses, exclusive and continued breastfeeding duration was longer for SSC than care-as-usual dyads (exclusive: 4.89 ± 1.26 vs. 3.25 ± 1.80 months; adjusted mean difference 1.28, 95% CI 0.31–2.24; p = 0.01; continued: 10.81 ± 1.97 vs. 6.98 ± 4.08 months; adjusted mean difference 2.33, 95% CI 0.13–4.54; p = 0.04). Exploratory dose–response effects indicated that more SSC hours predicted longer exclusive and continued breastfeeding duration. This study demonstrates that for the total group, the 5-week daily SSC intervention did not extend exclusive and continued breastfeeding duration. However, for mothers performing a regular daily hour of SSC, this simple and accessible intervention may extend exclusive and continued breastfeeding duration by months. Future studies are required to confirm these promising findings. Trial registration: Netherlands Trial Register (NTR5697).     

Improvement of patient localization repeatability using a light-section based optical surface guidance system in a pre-positioning procedure

PurposeSurface-guided radiotherapy is useful for the pre-positioning and monitoring of radiotherapy. The purpose of this study was to investigate the impact of surface guidance on the repeatability of patient localization and to estimate the specific point at which high positional errors occur.Materials and methodsTen patients without the VOXELAN system (non-VXLN group) and 10 patients with the VOXELAN as the pre-positioning procedure (VXLN group) were included in this analysis. Twelve regions of interest (ROI) were defined in all the patients to verify any misalignment during radiotherapy. Thirteen ROIs were defined on the isocenter.ResultsCompared with the non-VXLN group, the translational positional errors of the VXLN group were the same for all the ROIs. The mean translational positional errors of the VXLN group in the longitudinal direction were approximately 0.1 mm, and the standard deviation was the largest among the three directions in all the ROIs. The magnitude of the standard deviation in the non-VXLN group varied independently of the ROI and direction. The standard deviations of the VXLN group in the longitudinal direction were large in all the ROIs, while the standard deviations in the vertical and lateral directions were small.ConclusionPre-positioning with a surface guidance system reduced the body twist and rotation, which could not be corrected by image-guided radiotherapy alone. Since the VOXELAN can detect positioning errors quickly and without additional radiation exposure to the patient, it can be used as a tool for pre-positioning in radiotherapy.     

Internet of things-based health monitoring system for early detection of cardiovascular events during COVID-19 pandemic

The coronavirus disease 2019 (COVID-19) has currently caused the mortality of millions of people around the world. Aside from the direct mortality from the COVID-19, the indirect effects of the pandemic have also led to an increase in the mortality rate of other non-COVID patients. Evidence indicates that novel COVID-19 pandemic has caused an inflation in acute cardiovascular mortality, which did not relate to COVID-19 infection. It has in fact increased the risk of death in cardiovascular disease (CVD) patients. For this purpose, it is dramatically inevitable to monitor CVD patients’ vital signs and to detect abnormal events before the occurrence of any critical conditions resulted in death. Internet of things (IoT) and health monitoring sensors have improved the medical care systems by enabling latency-sensitive surveillance and computing of large amounts of patients’ data. The major challenge being faced currently in this problem is its limited scalability and late detection of cardiovascular events in IoT-based computing environments. To this end, this paper proposes a novel framework to early detection of cardiovascular events based on a deep learning architecture in IoT environments. Experimental results showed that the proposed method was able to detect cardiovascular events with better performance (95.30% average sensitivity and 95.94% mean prediction values).     

出生缺陷监测进展

利用科学、合理的监测手段对出生缺陷进行长期、持续的动态观察,有助于及时获悉缺陷发病率和疾病顺位的变化趋势,分析原因,为制定出生缺陷防控策略措施提供科学依据。本文综述了国内外出生缺陷的监测模式、监测病种和监测期限的工作进展。     

Attenuation Coefficient Estimation of Normal Placentas

Attenuation coefficient estimation has the potential to be a useful tool for placental tissue characterization. A current challenge is the presence of inhomogeneities in biological tissue that result in a large variance in the attenuation coefficient estimate (ACE), restricting its clinical utility. In this work, we propose a new Attenuation Estimation Region Of Interest (AEROI) selection method for computing the ACE based on the (i) envelope signal-to-noise ratio deviation and (ii) coefficient of variation of the transmit pulse bandwidth. The method was first validated on a tissue-mimicking phantom, for which an 18%–21% reduction in the standard deviation of ACE and a 14%–24% reduction in the ACE error, expressed as a percentage of reported ACE, were obtained. A study on 59 post-delivery clinically normal placentas was then performed. The proposed AEROI selection method reduced the intra-subject standard deviation of ACE from 0.72 to 0.39 dB/cm/MHz. The measured ACE of 59 placentas was 0.77 ± 0.37 dB/cm/MHz, which establishes a baseline for future studies on placental tissue characterization.     

Different triage categorization using Emergency Severity Index (ESI) method in emergency department

Objective

Triage is basically a categorization process to prioritize various treatments for patients based on the types of disease, severity, prognosis and resource availability. However, the term triage is more appropriate to be used in the context of natural disaster or mass casualties. Within the context of emergency situation in emergency department, the term triage refers to a method used to assess the severity of patients’ condition, determine the level of priority, and mobilize the patients to the suitable care unit. ESI is a new concept of triage using five scales in classifying the patients in emergency department. The real implementation of this concept demands nurses have to immediately make assessment about patients’ condition right away, besides they must give their final decision, whether to move the patients to the ward or to let them leave the hospital.